AI-Powered Adaptive Learning: Improving On-the-Job Training

Scalability is a make-or-break factor in expanding businesses. Companies that have scalable processes are more likely to be able to grow, achieve economies of scale, and outperform their competitors.

Outdated training programs are often an obstacle when it comes to achieving scale. A low-tech paper-based system might work with 100 employees, but not 100,000.

One of our clients, an entertainment company, faced this exact problem. They were highly dependent on their thousands of frontline workers to perform at a high level for customers. However, their outdated training program failed to organize information efficiently. Managers and trainers often had little idea who had learned what, and updating information was slow and costly.

Fortunately, by implementing Realizeit into their training program, they were able to improve efficiency and make it easier for managers to schedule workers based on their level of training. Realizeit’s personalized and adaptive learning system is perfect for structuring on-the-job training.

Case Study: On-the-Job Training in the Entertainment Industry

Our client was a world-class entertainment organization that ran a theme park. The frontline workers at the theme park were literally the face of the company, so they had extremely high standards for training.

In total, over 100,000 employees were trained for 500 jobs, mostly through on-the-job training. The company's existing training program was outdated and had limited ability to scale with the company as it grew.

Our efforts were able to dramatically improve their results. Now they are saving 10% on their overall training budget, just on efficiencies gained from improving training updates alone.

Problems with Existing On-the-Job Training

The existing on-the-job training program was mostly paper-based: binders, folders, and more kept track of what needed to be learned, and who had learned what. While this might work acceptably for a small organization, it was not at all suitable for a large, rapidly growing company that was extremely dependent on their frontline workers.

Updating any part of the training program used to require updating almost the whole thing. Trainers had to come in and sit down with employees, going through everything they had already learned, and detailing what had changed. Needless to say, this was incredibly inefficient. It was also difficult to schedule workers based on the skills they had learned, since the training program did a poor job of tracking learner abilities.

How Adaptive Learning Improved On-the-Job Training

Our solution was to create a structured on-the-job training program that tracked skills and made cross-training far more efficient. Now the company is able to take a much more targeted approach. Realizeit’s solution identifies what each learner has already learned as well as what is new. These updates can be pinpointed so that maintenance costs of the training program have been cut in half.

Trainers now have a better sense of what each learner knows. Before they begin training a worker, managers have a clear picture of how best to help them, taking into account the knowledge and skills the worker has previously acquired.

In addition, the system automatically guides learners back to refresh and update what they know. Trainers can see the areas where each individual learner is weak, and recommend additional training.

Realizeit and Scheduling

Realizeit has also integrated with the company's scheduling system so that untrained workers will not be able to be scheduled to work. Managers can now measure and know what skills people have learned, and where they are in or out of compliance, directly through the scheduling program.

Managers can also look at the interface if they need someone to do a job and determine who is closest to learning the job. If one employee has already learned most of the individual skills needed for a particular role, then the manager can pick them to train for performing that role.

Outcomes of Implementing Realizeit's Adaptive Learning Technology

Ultimately, Realizeit has given the client much more insight into their own training program and their own employees' strengths and weaknesses.

The system helps managers answer questions like the following:

• Do I have enough people ready to operate this part of the business?

• Do I need to get more people for this role?

• How many people are working today? And on what jobs?

• Are there people that have knowledge close to this job that I need to bring on and train them quickly?

This valuable information provides a lot of insight into risk, as well as adding flexibility to the company's operations. Whereas before this information was poorly integrated into the company’s operations, now it is readily accessible to the relevant stakeholders.

Conclusion: Modernizing On-the-Job Training with Realizeit

The Realizeit platform provides an AI-based adaptive learning solution for a variety of situations, including onboarding, upskilling, and on-the-job training.

When it comes to on-the-job training, many companies find themselves stuck. On one hand, on-the-job training is different from classroom training—it is based on raw experience in the field, not lectures and tests. But on the other hand, performance and ability still have to be measured. Lack of ability to measure this performance can lead to problems with allocating competently trained workers in a timely and efficient manner.

Adaptive systems like Realizeit are important for reducing redundancy and providing the measurable results that on-the-job training really needs. Our system maintains a real-time understanding of each learner's knowledge history, to determine what they know, and what they need to study. It does so on the job and in the classroom.

Our mission is to transform workforce training and learning through AI-driven personalization. If you would like to start a conversation, learn more about us, or hear about how other organizations use Realizeit's adaptive learning program, feel free to reach out and connect with a team who is eager to solve your training challenges. 

We hope to help you make personalized learning a key component of your organization’s training strategy!